{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T09:38:18Z","timestamp":1758274698361},"publisher-location":"Cham","reference-count":20,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030280604"},{"type":"electronic","value":"9783030280611"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-28061-1_20","type":"book-chapter","created":{"date-parts":[[2019,8,6]],"date-time":"2019-08-06T09:04:59Z","timestamp":1565082299000},"page":"186-198","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["PGCAS: A Parallelized Graph Clustering Algorithm Based on Spark"],"prefix":"10.1007","author":[{"given":"Dongjiang","family":"Liu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianhui","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,8,7]]},"reference":[{"issue":"7655","key":"20_CR1","doi-asserted-by":"publisher","first-page":"505","DOI":"10.1038\/nature22366","volume":"545","author":"EL Huttlin","year":"2017","unstructured":"Huttlin, E.L., Bruckner, R.J., Paulo, J.A., et al.: Architecture of the human interactome defines protein communities and disease networks. Nature 545(7655), 505 (2017)","journal-title":"Nature"},{"issue":"1","key":"20_CR2","doi-asserted-by":"publisher","first-page":"277","DOI":"10.1111\/cgf.12512","volume":"34","author":"C Vehlow","year":"2015","unstructured":"Vehlow, C., Beck, F., Auw\u00e4rter, P., et al.: Visualizing the evolution of communities in dynamic graphs. Comput. Graphics Forum 34(1), 277\u2013288 (2015)","journal-title":"Comput. Graphics Forum"},{"issue":"4","key":"20_CR3","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1145\/347057.347412","volume":"30","author":"B Krishnamurthy","year":"2000","unstructured":"Krishnamurthy, B., Wang, J.: On network-aware clustering of web clients. ACM SIGCOMM Comput. Commun. Rev. 30(4), 97\u2013110 (2000)","journal-title":"ACM SIGCOMM Comput. Commun. Rev."},{"key":"20_CR4","doi-asserted-by":"crossref","unstructured":"Wickramaarachchi, C., Frincu, M., Small, P., et al.: Fast parallel algorithm for unfolding of communities in large graphs. In: High Performance Extreme Computing Conference (HPEC), pp. 1\u20136. IEEE (2014)","DOI":"10.1109\/HPEC.2014.7040973"},{"key":"20_CR5","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1016\/j.parco.2015.03.003","volume":"47","author":"H Lu","year":"2015","unstructured":"Lu, H., Halappanavar, M., Kalyanaraman, A.: Parallel heuristics for scalable community detection. Parallel Comput. 47, 19\u201337 (2015)","journal-title":"Parallel Comput."},{"key":"20_CR6","unstructured":"Moon, S., Lee, J.G., Kang, M.: Scalable community detection from networks by computing edge betweenness on MapReduce. In: International Conference on Big Data and Smart Computing (BIGCOMP), pp. 145\u2013148. IEEE (2014)"},{"issue":"3\/4","key":"20_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1147\/JRD.2013.2251982","volume":"57","author":"J Shi","year":"2013","unstructured":"Shi, J., Xue, W., Wang, W., et al.: Scalable community detection in massive social networks using MapReduce. IBM J. Res. Dev. 57(3\/4), 1\u201312 (2013)","journal-title":"IBM J. Res. Dev."},{"key":"20_CR8","first-page":"359","volume":"53","author":"Y Chen","year":"2009","unstructured":"Chen, Y., Huang, C., Zhai, K.: Scalable community detection algorithm with MapReduce. Commun. ACM 53, 359\u2013366 (2009)","journal-title":"Commun. ACM"},{"issue":"12","key":"20_CR9","doi-asserted-by":"publisher","first-page":"7821","DOI":"10.1073\/pnas.122653799","volume":"99","author":"M Girvan","year":"2002","unstructured":"Girvan, M., Newman, M.E.J.: Community structure in social and biological networks. Proc. Nat. Acad. Sci. 99(12), 7821\u20137826 (2002)","journal-title":"Proc. Nat. Acad. Sci."},{"issue":"5","key":"20_CR10","doi-asserted-by":"publisher","first-page":"e1602548","DOI":"10.1126\/sciadv.1602548","volume":"3","author":"L Peel","year":"2017","unstructured":"Peel, L., Larremore, D.B., Clauset, A.: The ground truth about metadata and community detection in networks. Sci. Adv. 3(5), e1602548 (2017)","journal-title":"Sci. Adv."},{"issue":"3","key":"20_CR11","doi-asserted-by":"publisher","first-page":"033015","DOI":"10.1088\/1367-2630\/11\/3\/033015","volume":"11","author":"A Lancichinetti","year":"2009","unstructured":"Lancichinetti, A., Fortunato, S., Kertsz, J.: Detecting the overlapping and hierarchical community structure in complex networks. New J. Phys. 11(3), 033015 (2009)","journal-title":"New J. Phys."},{"issue":"6","key":"20_CR12","first-page":"50","volume":"81","author":"H Abdelbary","year":"2013","unstructured":"Abdelbary, H., El-Korany, A.: Semantic topics modeling approach for community detection. Int. J. Comput. Appl. 81(6), 50\u201358 (2013)","journal-title":"Int. J. Comput. Appl."},{"key":"20_CR13","doi-asserted-by":"crossref","unstructured":"Nguyen, T., Phung, D., Adams, B., et al.: Hyper-community detection in the blogosphere. In: Proceedings of Second ACM SIGMM Workshop on Social Media, pp. 21\u201326. ACM (2010)","DOI":"10.1145\/1878151.1878159"},{"issue":"10","key":"20_CR14","doi-asserted-by":"publisher","first-page":"P10012","DOI":"10.1088\/1742-5468\/2004\/10\/P10012","volume":"2004","author":"L Donetti","year":"2004","unstructured":"Donetti, L., Munoz, M.A.: Detecting network communities: a new systematic and efficient algorithm. J. Stat. Mech: Theory Exp. 2004(10), P10012 (2004)","journal-title":"J. Stat. Mech: Theory Exp."},{"issue":"3","key":"20_CR15","doi-asserted-by":"publisher","first-page":"686","DOI":"10.1017\/apr.2017.18","volume":"49","author":"L Gulikers","year":"2017","unstructured":"Gulikers, L., Lelarge, M., Massouli\u00e9, L.: A spectral method for community detection in moderately sparse degree-corrected stochastic block models. Adv. Appl. Probab. 49(3), 686\u2013721 (2017)","journal-title":"Adv. Appl. Probab."},{"issue":"5","key":"20_CR16","doi-asserted-by":"publisher","first-page":"052808","DOI":"10.1103\/PhysRevE.92.052808","volume":"92","author":"X Zhang","year":"2015","unstructured":"Zhang, X., Newman, M.E.J.: Multiway spectral community detection in networks. Phys. Rev. E 92(5), 052808 (2015)","journal-title":"Phys. Rev. E"},{"key":"20_CR17","volume-title":"Matrix Computations","author":"GH Golub","year":"1996","unstructured":"Golub, G.H., Van Loan, C.F.: Matrix Computations. Johns Hopkins University Press, Baltimore (1996)"},{"issue":"P1","key":"20_CR18","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1016\/j.comnet.2016.06.002","volume":"107","author":"Q Zhang","year":"2016","unstructured":"Zhang, Q., Qiu, Q., Guo, W., et al.: A social community detection algorithm based on parallel grey label propagation. Comput. Netw. 107(P1), 133\u2013143 (2016)","journal-title":"Comput. Netw."},{"issue":"2","key":"20_CR19","doi-asserted-by":"publisher","first-page":"026113","DOI":"10.1103\/PhysRevE.69.026113","volume":"69","author":"MEJ Newman","year":"2004","unstructured":"Newman, M.E.J., Girvan, M.: Finding and evaluating community structure in networks. Phys. Rev. E 69(2), 026113 (2004)","journal-title":"Phys. Rev. E"},{"issue":"10\u201310","key":"20_CR20","first-page":"95","volume":"10","author":"M Zaharia","year":"2010","unstructured":"Zaharia, M., Chowdhury, M., Franklin, M.J., et al.: Spark: cluster computing with working sets. HotCloud 10(10\u201310), 95 (2010)","journal-title":"HotCloud"}],"container-title":["Lecture Notes in Computer Science","Big Scientific Data Management"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-28061-1_20","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,6]],"date-time":"2019-08-06T09:13:06Z","timestamp":1565082786000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-28061-1_20"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030280604","9783030280611"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-28061-1_20","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"7 August 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"BigSDM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Big Scientific Data Management","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Beijing","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 November 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1 December 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"bigsdm2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/bigsdm2018.csdata.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"86","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"24","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"7","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"28% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}